The accurate prediction of reaction kinetics data, e.g., reaction rate constants, for the microgel synthesis is highly desired because its usage in model-based design approaches promises the development of more specialized microgels and enables new applications. The complexity and the diversity of the microgel synthesis, however, often prevent experimental approaches but depict challenges for prediction approaches, as well. Therefore, this thesis analyzes a wide range of aspects relevant for the microgel synthesis individually and proposes prediction strategies for each. Here, the focus is on three main aspects: (i) The prediction of reaction kinetics in homogenous liquid reaction environments by combining high-level density functional theory and COSMO-RS, (ii) improving the property prediction of ionic species by applying the Cluster-Continuum approach and analyzing the uncertainty of the reference data, and (iii) enabling the kinetics prediction for inhomogeneous reaction environments with ReaxFF reactive molecular dynamics (MD) simulations. The results show that macroscopic properties of microgels, e.g., the crosslinker distribution, can be linked to the elementary reaction kinetics. In addition, the prediction of the solvation free energy of ionic solutes dissolved in neutral solvents is achieved with a deviation of just 2.0 kcal mol−1, which removes a main bottleneck for reaction kinetics prediction of such ionic systems. Furthermore, analyzing the statistical uncertainty of rare events in reactive MD simulations revealed that just a few reaction events are sufficient to obtain rate constants of sufficient quality. This is a key finding for the study of the microgel synthesis in reactive MD simulations because the required large system sizes and limited computational resources prevent the observation of more events practically. Also, force fields and their parametrizations should be evaluated regarding the eligibility for studying the microgel synthesis reactions based on the correct description of the vinyl group. In total, this thesis develops and presents a toolbox for reaction kinetics predictions for the microgel synthesis.